The associating of parameters also makes it possible to characterize a transmitter by its signal-to-noise ratio. It is also possible to characterize an FH (Frequency Hopping) by its plateau durations, its frequencies of appearance and its direction of arrival. A modulation can also be characterized by identifying for example its amplitude state and phase state.
FIG. 1 illustrates airborne location with a mobile reception system, the transmitter 1 is at the position (x0, y0, z0), the carrier 2 at the instant tk is at the position (xk, yk, zk) and sees the transmitter 1 at the angle of incidence (θ(tk, x0, y0, z0), Δ(tk, x0, y0, z0)). The angles θ(t, x0, y0, z0) and Δ(t, x0, y0, z0) evolve over time and depend on the position of the transmitter and also the trajectory of the reception system. The angles θ(t, x0, y0, z0) and Δ(t, x0, y0, z0) are charted with the aid of an array of N antennas that can be fixed under the carrier as shown by FIG. 2.
The antennas Ai of the array receive the sources with a phase and amplitude that depend on the angle of incidence of the sources and also the position of the antennas.
Antenna processing techniques generally utilize the spatial diversity of the sources (or transmitters): use of the spatial position of the antennas of the array to better utilize the differences in incidence and in distance of the sources. Antenna processing breaks down into two main areas of activity:
1—Spatial filtering, illustrated in FIG. 3, the objective of which is to extract either the modulated signals sm(t), or the symbols contained in the signal (Demodulation). This filtering consists in combining the signals received on the array of sensors so as to form an optimal reception antenna for one of the sources. Spatial filtering can be blind or cooperative.It is cooperative when there is a priori knowledge about the transmitted signals (directions of arrival, symbol sequences, etc.) and it is blind in the contrary case. It is used for blind source separation, filtering matched to direction of arrival (beam formation) or to replicas, multi-sensor MODEM (demodulation), etc.2—The objective of estimating the parameters of the transmitters is to determine various parameters such as: their Doppler frequencies, their bit rates, their modulation indices, their positions (xm,ym), their incidences (θm,Δm) and their direction vectors a(θm,Δm) (response of the array of sensors to a source with direction (θm,Δm)) etc.
For example, goniometry and blind identification procedures exist in this area:
The objective of goniometry is to determine the incidences θ(t, xm, ym, zm) in 1D or the pair of incidences (θ(t, xm, ym, zm),Δ(t, xm, ym, zm)) in 2D. For this purpose, goniometry algorithms use the observations arising from the antennas or sensors. When the waves from all the transmitters propagate in the same plane, it suffices to apply a 1D goniometry, in other cases, a 2D goniometry.
The objective of blind identification procedures (ICA) is notably to determine the direction vectors a(θm,Δm) of each of the transmitters.
The known location techniques according to the prior art generally use histogram techniques to group the parameters together. However, these techniques have the drawback of requiring a priori knowledge about the standard deviation of the parameters in order to fix the stepsize of the histogram.